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Paper Citation Record · LEDGER

Analysis of quantum neural network performance via edge cases

As of 23 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.12427.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.12427 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:56:19.810111Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

  • verified exact4
  • verified fuzzy4
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 062ee252-1190-4eaa-9697-2212f8880f50 · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

Analysis of quantum neural network performance via edge cases PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:18.655513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:18.655513Z digest=sha256:3fda8422079abad5a3dd4dadf0b47376eddf78ab370766131e55fc61d4a4f3cf

Observation 2a7b44fe-e0c3-459b-b894-3e7087a90cb3 · outbound

This paper cites Learning surrogate models for simulation-based optimization,.

Analysis of quantum neural network performance via edge cases Learning surrogate models for simulation-based optimization,

Reference 2

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unresolved
no resolver link, observed 2026-08-07T00:56:18.716022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:18.716022Z digest=sha256:6f42c083cb00f295f922941ef17a7ad1015645722e9721aaccf609b6e28218b7

Observation 82e49996-8500-4a87-97ca-b53929f9a09a · outbound

This paper cites Performance evaluation of different machine learning techniques for prediction of heart disease,.

Analysis of quantum neural network performance via edge cases Performance evaluation of different machine learning techniques for prediction of heart disease,

Reference 3

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verified exact
doi, observed 2026-08-07T00:56:20.436709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 06cbf7fa-68bb-4e37-9889-828c845b2938 · outbound

This paper cites On random graphs. I.

Analysis of quantum neural network performance via edge cases On random graphs. I

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.854498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T00:56:18.869525Z digest=sha256:91e4751e436f8e12217689dd5d3c232f285892d9b715630a4f7580164f32c6d7

Observation f3600e78-8277-4f24-8f9e-f5cf237bbffe · outbound

This paper cites Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward,.

Analysis of quantum neural network performance via edge cases Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.611066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T00:56:18.968354Z digest=sha256:2cc1714d99065e50392c6a913b569f3bfe5c656b42178aa9fb79116c779d8e32

Observation 2100e82f-f6a5-4adf-b6e6-8378ff2e21f7 · outbound

This paper cites Performance Evaluation in Machine Learning,.

Analysis of quantum neural network performance via edge cases Performance Evaluation in Machine Learning,

Reference 6

Resolution
verified exact
doi, observed 2026-08-07T00:56:20.208751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T00:56:19.085746Z digest=sha256:b0c3d8a4bda207afb7b119ac5b1b80c10244656a9877ecbc8c3aaa6f6bdab0ec

Observation 1387093a-c641-42db-bad2-ce50b7c84421 · outbound

This paper cites Performance measures in evaluating machine learning based bioinformatics predictors for classifications,.

Analysis of quantum neural network performance via edge cases Performance measures in evaluating machine learning based bioinformatics predictors for classifications,

Reference 7

Resolution
verified exact
doi, observed 2026-08-07T00:56:20.070689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T00:56:19.168261Z digest=sha256:20d49bbd92b08a21c8d911a962e5b0ba3bd89360a8f1a1451f1c632b60d49c10

Observation 8c8173d4-8341-44f9-bc1d-4afc5becd755 · outbound

This paper cites Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques,.

Analysis of quantum neural network performance via edge cases Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.377067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T00:56:19.262165Z digest=sha256:3a1b23eeb3e6c64cb0e905b3315ef44de11edc2c6a4a679ea419346687574817

Observation 87a2db32-3e9b-486f-8027-c113b6ff3759 · outbound

This paper cites Permutation-invariant quantum circuits.

Analysis of quantum neural network performance via edge cases Permutation-invariant quantum circuits

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.351693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.351693Z digest=sha256:fee07ce41fa775860f4e6f768a5f89d947692217fb63769235482fd78a2b3fd9

Observation 19537e63-1db5-4a61-b3b8-1b372ed8fe4d · outbound

This paper cites Scaling of symmetry-restricted quantum circuits.

Analysis of quantum neural network performance via edge cases Scaling of symmetry-restricted quantum circuits

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.406110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.406110Z digest=sha256:d03ef5c48dac17b0ba72c0a61b50218c0510a6b20662d5f1fafa62b0185f1abb

Observation f4b28ae2-fad4-453f-8f41-4cb06e248e1f · outbound

This paper cites Solving graph problems using permutation-invariant quantum machine learning.

Analysis of quantum neural network performance via edge cases Solving graph problems using permutation-invariant quantum machine learning

Reference 11

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verified exact
local_arxiv, observed 2026-08-07T00:56:20.676969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 64f1fde5-05dc-4b58-adcf-c4a49108949f · outbound

This paper cites A Review of Evaluation Metrics in Machine Learning Algorithms,.

Analysis of quantum neural network performance via edge cases A Review of Evaluation Metrics in Machine Learning Algorithms,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.630070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.630070Z digest=sha256:8852bb690a4818090c7dd58c8cddced3d2e5952d4bc7c96b35fa062cf0a8958f

Observation 8e3344fe-8693-47c1-95a5-4708fff7f3be · outbound

This paper cites Machine learning and uncertainty quantification for surrogate models of integrated devices with a large number of parameters,.

Analysis of quantum neural network performance via edge cases Machine learning and uncertainty quantification for surrogate models of integrated devices with a large number of parameters,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:56:21.050670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T00:56:19.718668Z digest=sha256:f77fbe73c5697eaa3c1ecc02a61b48c5b53c4ac11ee6a66bf2f4dc566ac1315f

Observation 7a9aed22-f766-4e11-9511-8e3bd6c0246a · outbound

This paper cites Evaluating Machine Learning Models and Their Diagnostic Value,.

Analysis of quantum neural network performance via edge cases Evaluating Machine Learning Models and Their Diagnostic Value,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:19.810111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:56:19.810111Z digest=sha256:87b9d2853773337abbc1d6e2e61e3fb7d8d1e0af8970b0693c0a6dc3a9d340d2

Pith citing papers

No inbound Pith citation observations are available.